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COINTURK FINANCE > Startup > BuiltAI Secures $6 Million to Modernize Real Estate Investment
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BuiltAI Secures $6 Million to Modernize Real Estate Investment

Overview

  • BuiltAI raised $6 million for enhancing real estate financial modeling.

  • Platform uses AI to improve investment screening efficiency and accuracy.

  • Funding supports U.S. and U.K. expansion and platform upgrades.

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BuiltAI, a company specializing in financial modeling for commercial real estate investments, has captured the spotlight by raising $6 million in seed funding. The investment round, steered by the New York-based VC firm Work-Bench, includes participation from Lerer Hippeau, Timber Grove Ventures, and Emerald Pine. This funding aims to pave a new path in the commercial real estate sector, presenting innovative solutions to the age-old manual processes tapping into the $26 billion real estate software market.

Contents
How Outdated Are Current Processes?What is BuiltAI’s Solution?

How Outdated Are Current Processes?

While real estate software sees substantial investment, most procedures in investment screening and financial modeling rely on manual steps, such as data entry into spreadsheets. Despite this reliance, these manual processes are prone to errors, with 88% of financial models containing material inaccuracies. These inefficiencies lead to prolonged analysis times, up to two weeks, potentially causing missed investment opportunities.

What is BuiltAI’s Solution?

Founded in 2020 by Natan Lempert and Firoz Noordeen, BuiltAI uses machine learning to transform building data analysis. The platform allows investors to generate detailed financial models quickly, enabling the formulation of comprehensive business plans. This technology not only saves time but offers significant improvements over existing processes by encompassing diverse data points like real estate fundamentals and local market conditions.

In earlier explorations of real estate investment technologies, several platforms attempted to automate various aspects of real estate management. However, BuiltAI distinguishes itself with its focus on using advanced AI to streamline the vast data involved in underwriting real estate deals. Analysts have noted the struggle of other tools to keep up with the multidimensional nature of property investment, setting BuiltAI apart in its approach.

Generative AI, a significant component of BuiltAI’s offering, is increasingly influencing financial decision-making.

Real estate is the world’s largest asset class, yet the evaluative tools have remained virtually unchanged for decades.

According to Lempert, incorporating AI in this sector is overdue, as it allows for large-scale data processing and automation of complex underwriting processes. BuiltAI’s AI solution has the potential to redefine asset lifecycle management for brokers, investors, lenders, and valuers.

The latest funding will enable BuiltAI to expand its U.S. and U.K. operations while bolstering its platform’s capabilities. This financial backing also coincides with the introduction of their asset management tool, designed to offer real-time scenario analysis and streamline decision-making for real estate owners.

Although previous tools addressed certain components of property management, BuiltAI provides a more holistic approach. Its AI-driven technology aims to overcome long-standing inefficiencies, moving towards a future where real estate transactions and management experience higher precision and speed.

Efforts to modernize real estate investment tools have had mixed success over the years. Yet, BuiltAI’s approach focuses on comprehensive data analysis and quick financial modeling, targeting common pain points in investment deal screenings. This seed funding round indicates a strong belief in BuiltAI’s capacity to offer a viable solution to longstanding issues in commercial real estate investment.

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Disclaimer: The information contained in this article does not constitute investment advice. Investors should be aware that cryptocurrencies carry high volatility and therefore risk, and should conduct their own research.

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